Explainable deep learning with Shapley additive explanations for multivariate wind power forecasting

Wind is a popular renewable energy source, but it is highly dependent on environmental conditions and internal dynamics. Given these complexities, the need for accurate forecasting models that account for multiple variables is critical. However, the challenge extends beyond accuracy to the interpret...

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Bibliografiska uppgifter

Huvudupphov:	Ege Kandemir, Dilip Kumar Prasad, Agus Hasan, Trond Kvamsdal, Saleh Abdel-Afou Alaliyat
Materialtyp:	Artigo
Språk:	Inglês
Utgiven:	Elsevier 2026-05-01
Serie:	Energy Conversion and Management: X
Ämnen:	Stacked bidirectional LSTM Interpretability Explainable artificial intelligence (XAI) Model transparency SHAP Wind energy
Länkar:	http://www.sciencedirect.com/science/article/pii/S2590174526003843
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